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Identifying differences in wet and dry road crashes using data mining

Emerson, Daniel , Nayak, Richi, Weligamage, Justin , & Piyatrapoomi, Noppadol (2011) Identifying differences in wet and dry road crashes using data mining. In World Congress on Engineering Asset Management (WCEAM 2010), 25‐27 October 2010, Brisbane, Australia. (In Press)

Abstract

It is commonly accepted that wet roads have higher risk of crash than dry roads; however, providing evidence to support this assumption presents some difficulty. This paper presents a data mining case study in which predictive data mining is applied to model the skid resistance and crash relationship to search for discernable differences in the probability of wet and dry road segments having crashes based on skid resistance. The models identify an increased probability of wet road segments having crashes for mid-range skid resistance values.

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103 since deposited on 19 Apr 2011
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ID Code: 41354
Item Type: Conference Paper
Keywords: road crashes, road accidents, wet road crashes, dry road crashes, data mining
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2010 [please consult authors]
Deposited On: 19 Apr 2011 12:43
Last Modified: 11 Aug 2011 04:14

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